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<title>Doxygen: pcl::rec_3d_framework::GlobalNNCVFHRecognizer&lt; Distance, PointInT, FeatureT &gt; 模板类 参考</title>
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<a href="#nested-classes">类</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-types">Protected 类型</a> &#124;
<a href="#pro-methods">Protected 成员函数</a> &#124;
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<div class="title">pcl::rec_3d_framework::GlobalNNCVFHRecognizer&lt; Distance, PointInT, FeatureT &gt; 模板类 参考</div>  </div>
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<p>Nearest neighbor search based classification of PCL point type features. Available features: CVFH  
 <a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="global__nn__recognizer__cvfh_8h_source.html">global_nn_recognizer_cvfh.h</a>&gt;</code></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
类</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1flann__model.html">flann_model</a></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1index__score.html">index_score</a></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1sort_index_scores.html">sortIndexScores</a></td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a069bb2303c97d572a8af3664d37ffdfc"><td class="memItemLeft" align="right" valign="top"><a id="a069bb2303c97d572a8af3664d37ffdfc"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><b>getDescriptorDistances</b> (std::vector&lt; float &gt; &amp;ds)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setComputeScale</b> (bool d)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setCategoriesToUseForRecognition</b> (std::vector&lt; std::string &gt; &amp;cats_to_use)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setUseSingleCategories</b> (bool b)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setNoise</b> (float n)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setNN</b> (int nn)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setICPIterations</b> (int it)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a368da06e74208da29417127f8ec89cbf">initialize</a> (bool force_retrain=false)</td></tr>
<tr class="memdesc:a368da06e74208da29417127f8ec89cbf"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initializes the FLANN structure from the provided source <br /></td></tr>
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<tr class="memitem:ae8947c5b116adb3bd4f5baabdd9a501a"><td class="memItemLeft" align="right" valign="top"><a id="ae8947c5b116adb3bd4f5baabdd9a501a"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#ae8947c5b116adb3bd4f5baabdd9a501a">setDataSource</a> (typename boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_source.html">Source</a>&lt; PointInT &gt; &gt; &amp;source)</td></tr>
<tr class="memdesc:ae8947c5b116adb3bd4f5baabdd9a501a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the model data source_ <br /></td></tr>
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<tr class="memitem:a525d05d96b32a9ffea2366d53259a099"><td class="memItemLeft" align="right" valign="top"><a id="a525d05d96b32a9ffea2366d53259a099"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a525d05d96b32a9ffea2366d53259a099">setFeatureEstimator</a> (typename boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_o_u_r_c_v_f_h_estimator.html">OURCVFHEstimator</a>&lt; PointInT, FeatureT &gt; &gt; &amp;feat)</td></tr>
<tr class="memdesc:a525d05d96b32a9ffea2366d53259a099"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the model data source_ <br /></td></tr>
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<tr class="memitem:ac7dd9a5e980e7aa63ab4d604047c34cd"><td class="memItemLeft" align="right" valign="top"><a id="ac7dd9a5e980e7aa63ab4d604047c34cd"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#ac7dd9a5e980e7aa63ab4d604047c34cd">setHVAlgorithm</a> (typename boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_hypothesis_verification.html">HypothesisVerification</a>&lt; PointInT, PointInT &gt; &gt; &amp;alg)</td></tr>
<tr class="memdesc:ac7dd9a5e980e7aa63ab4d604047c34cd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the HV algorithm <br /></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setIndices</b> (std::vector&lt; int &gt; &amp;indices)</td></tr>
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<tr class="memitem:aaee9336762ba592fb54ed8c2560f4bd7"><td class="memItemLeft" align="right" valign="top"><a id="aaee9336762ba592fb54ed8c2560f4bd7"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#aaee9336762ba592fb54ed8c2560f4bd7">setInputCloud</a> (const PointInTPtr &amp;cloud)</td></tr>
<tr class="memdesc:aaee9336762ba592fb54ed8c2560f4bd7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the input cloud to be classified <br /></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setDescriptorName</b> (std::string &amp;name)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setTrainingDir</b> (std::string &amp;dir)</td></tr>
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<tr class="memitem:ac8b598342d94c4ae9d12b536370002af"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#ac8b598342d94c4ae9d12b536370002af">recognize</a> ()</td></tr>
<tr class="memdesc:ac8b598342d94c4ae9d12b536370002af"><td class="mdescLeft">&#160;</td><td class="mdescRight">Performs recognition on the input cloud  <a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#ac8b598342d94c4ae9d12b536370002af">更多...</a><br /></td></tr>
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boost::shared_ptr&lt; std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>getModels</b> ()</td></tr>
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boost::shared_ptr&lt; std::vector&lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt; Eigen::Matrix4f &gt; &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>getTransforms</b> ()</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setUseCache</b> (bool u)</td></tr>
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Protected 类型</h2></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointInTPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPointInTPtr</b></td></tr>
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typedef Distance&lt; float &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>DistT</b></td></tr>
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typedef <a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">Model</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ModelT</b></td></tr>
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Protected 成员函数</h2></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>loadFeaturesAndCreateFLANN</b> ()</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>convertToFLANN</b> (const std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1flann__model.html">flann_model</a> &gt; &amp;models, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt; &amp;data)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>convertToFLANN</b> (const std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1flann__model.html">flann_model</a> &gt; &amp;models, boost::shared_ptr&lt; std::vector&lt; int &gt; &gt; &amp;indices, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt; &amp;data)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>nearestKSearch</b> (<a class="el" href="classflann_1_1_index.html">flann::Index</a>&lt; DistT &gt; *index, const <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1flann__model.html">flann_model</a> &amp;model, int k, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; int &gt; &amp;indices, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt; &amp;distances)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getPose</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, Eigen::Matrix4f &amp;pose_matrix)</td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><b>getRollPose</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, int d_id, Eigen::Matrix4f &amp;pose_matrix)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getCentroid</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, int d_id, Eigen::Vector3f &amp;centroid)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getView</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, PointInTPtr &amp;view)</td></tr>
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Protected 属性</h2></td></tr>
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struct <a class="el" href="structpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_1_1sort_index_scores.html">pcl::rec_3d_framework::GlobalNNCVFHRecognizer::sortIndexScores</a>&#160;</td><td class="memItemRight" valign="bottom"><b>sortIndexScoresOp</b></td></tr>
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std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a1c39c77c0efe0fb4a7aad2163a6436f9">training_dir_</a></td></tr>
<tr class="memdesc:a1c39c77c0efe0fb4a7aad2163a6436f9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Directory where the trained structure will be saved <br /></td></tr>
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PointInTPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a44090665a54a815539d3bf286cfe00be">input_</a></td></tr>
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boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_o_u_r_c_v_f_h_estimator.html">OURCVFHEstimator</a>&lt; PointInT, FeatureT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8cfe49751fd78df3ea0591e380b8ef9d">micvfh_estimator_</a></td></tr>
<tr class="memdesc:a8cfe49751fd78df3ea0591e380b8ef9d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes a feature <br /></td></tr>
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std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#affffb23d7cc95b3a3ef63fed292bbb25">descr_name_</a></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><b>ICP_iterations_</b></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><b>noisify_</b></td></tr>
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float&#160;</td><td class="memItemRight" valign="bottom"><b>noise_</b></td></tr>
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<a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>flann_data_</b></td></tr>
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<a class="el" href="classflann_1_1_index.html">flann::Index</a>&lt; DistT &gt; *&#160;</td><td class="memItemRight" valign="bottom"><b>flann_index_</b></td></tr>
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std::vector&lt; std::string &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>categories_to_be_searched_</b></td></tr>
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boost::shared_ptr&lt; std::vector&lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt; Eigen::Matrix4f &gt; &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>transforms_</b></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;template&lt; class &gt; class Distance, typename PointInT, typename FeatureT = pcl::VFHSignature308&gt;<br />
class pcl::rec_3d_framework::GlobalNNCVFHRecognizer&lt; Distance, PointInT, FeatureT &gt;</h3>

<p>Nearest neighbor search based classification of PCL point type features. Available features: CVFH </p>
<dl class="section author"><dt>作者</dt><dd>Aitor Aldoma </dd></dl>
</div><h2 class="groupheader">成员函数说明</h2>
<a id="ac8b598342d94c4ae9d12b536370002af"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac8b598342d94c4ae9d12b536370002af">&#9670;&nbsp;</a></span>recognize()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;template&lt; class &gt; class Distance, typename PointInT , typename FeatureT &gt; </div>
      <table class="memname">
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          <td class="memname">void <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html">pcl::rec_3d_framework::GlobalNNCVFHRecognizer</a>&lt; Distance, PointInT, FeatureT &gt;::recognize</td>
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<p>Performs recognition on the input cloud </p>
<p>POSE REFINEMENT</p>
<p>HYPOTHESES VERIFICATION</p>
<div class="fragment"><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;  {</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160; </div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    models_.reset (<span class="keyword">new</span> std::vector&lt;ModelT&gt;);</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    transforms_.reset (<span class="keyword">new</span> std::vector&lt;Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt;);</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160; </div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    PointInTPtr processed (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    PointInTPtr in (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160; </div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    std::vector&lt;pcl::PointCloud&lt;FeatureT&gt;, Eigen::aligned_allocator&lt;pcl::PointCloud&lt;FeatureT&gt; &gt; &gt; signatures;</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    std::vector &lt; Eigen::Vector3f, Eigen::aligned_allocator&lt;Eigen::Vector3f&gt; &gt; centroids;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160; </div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="keywordflow">if</span> (indices_.size ())</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;      <a class="code" href="group__common.html#gaa65b1c8d782e7b776ae682679d2d948f">pcl::copyPointCloud</a> (*<a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a44090665a54a815539d3bf286cfe00be">input_</a>, indices_, *in);</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;      in = <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a44090665a54a815539d3bf286cfe00be">input_</a>;</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160; </div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    {</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Estimate feature&quot;</span>);</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8cfe49751fd78df3ea0591e380b8ef9d">micvfh_estimator_</a>-&gt;estimate (in, processed, signatures, centroids);</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    }</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160; </div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    std::vector&lt;index_score&gt; indices_scores;</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    descriptor_distances_.clear ();</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160; </div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    <span class="keywordflow">if</span> (signatures.size () &gt; 0)</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    {</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160; </div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;      {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t_matching (<span class="stringliteral">&quot;Matching and roll...&quot;</span>);</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160; </div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;        <span class="keywordflow">if</span> (use_single_categories_ &amp;&amp; (categories_to_be_searched_.size () &gt; 0))</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        {</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160; </div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;          <span class="comment">//perform search of the different signatures in the categories_to_be_searched_</span></div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> c = 0; c &lt; categories_to_be_searched_.size (); c++)</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;          {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Using category:&quot;</span> &lt;&lt; categories_to_be_searched_[c] &lt;&lt; std::endl;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> idx = 0; idx &lt; signatures.size (); idx++)</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;            {</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;              <span class="comment">/*float* hist = signatures[idx].points[0].histogram;</span></div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;<span class="comment">               std::vector&lt;float&gt; std_hist (hist, hist + getHistogramLength (dummy));</span></div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;<span class="comment">               flann_model histogram (&quot;&quot;, std_hist);</span></div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;<span class="comment">               flann::Matrix&lt;int&gt; indices;</span></div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;<span class="comment">               flann::Matrix&lt;float&gt; distances;</span></div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;<span class="comment">               std::map&lt;std::string, int&gt;::iterator it;</span></div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;<span class="comment">               it = category_to_vectors_indices_.find (categories_to_be_searched_[c]);</span></div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;<span class="comment">               assert (it != category_to_vectors_indices_.end ());</span></div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;<span class="comment">               nearestKSearch (single_categories_index_[it-&gt;second], histogram, nmodels_, indices, distances);*/</span></div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160; </div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;              <span class="keywordtype">float</span>* hist = signatures[idx].points[0].histogram;</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;              <span class="keywordtype">int</span> size_feat = <span class="keyword">sizeof</span>(signatures[idx].points[0].histogram) / <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>);</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;              std::vector&lt;float&gt; std_hist (hist, hist + size_feat);</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;              <span class="comment">//ModelT empty;</span></div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160; </div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;              flann_model histogram;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;              histogram.descr = std_hist;</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;              <a class="code" href="classflann_1_1_matrix.html">flann::Matrix&lt;int&gt;</a> indices;</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;              <a class="code" href="classflann_1_1_matrix.html">flann::Matrix&lt;float&gt;</a> distances;</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160; </div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;              std::map&lt;std::string, int&gt;::iterator it;</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;              it = category_to_vectors_indices_.find (categories_to_be_searched_[c]);</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;              assert (it != category_to_vectors_indices_.end ());</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160; </div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;              nearestKSearch (single_categories_index_[it-&gt;second], histogram, NN_, indices, distances);</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;              <span class="comment">//gather NN-search results</span></div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;              <span class="keywordtype">double</span> score = 0;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;              <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; NN_; ++i)</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;              {</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;                score = distances[0][i];</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;                index_score is;</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;                is.idx_models_ = single_categories_pointers_to_models_[it-&gt;second]-&gt;at (indices[0][i]);</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;                is.idx_input_ = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (idx);</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;                is.score_ = score;</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;                indices_scores.push_back (is);</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;              }</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;            }</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160; </div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;            <span class="comment">//we cannot add more than nmodels per category, so sort here and remove offending ones...</span></div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;            std::sort (indices_scores.begin (), indices_scores.end (), sortIndexScoresOp);</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;            indices_scores.resize ((c + 1) * NN_);</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;          }</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;        }</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;        <span class="keywordflow">else</span></div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;        {</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> idx = 0; idx &lt; signatures.size (); idx++)</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;          {</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;            <span class="keywordtype">float</span>* hist = signatures[idx].points[0].histogram;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;            <span class="keywordtype">int</span> size_feat = <span class="keyword">sizeof</span>(signatures[idx].points[0].histogram) / <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>);</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;            std::vector&lt;float&gt; std_hist (hist, hist + size_feat);</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;            <span class="comment">//ModelT empty;</span></div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160; </div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;            flann_model histogram;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;            histogram.descr = std_hist;</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160; </div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;            <a class="code" href="classflann_1_1_matrix.html">flann::Matrix&lt;int&gt;</a> indices;</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;            <a class="code" href="classflann_1_1_matrix.html">flann::Matrix&lt;float&gt;</a> distances;</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;            nearestKSearch (flann_index_, histogram, NN_, indices, distances);</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160; </div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;            <span class="comment">//gather NN-search results</span></div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;            <span class="keywordtype">double</span> score = 0;</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NN_; ++i)</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;            {</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;              score = distances[0][i];</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;              index_score is;</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;              is.idx_models_ = indices[0][i];</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;              is.idx_input_ = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (idx);</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;              is.score_ = score;</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;              indices_scores.push_back (is);</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160; </div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;              <span class="comment">//ModelT m = flann_models_[indices[0][i]].model;</span></div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;            }</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;          }</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        }</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160; </div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;        std::sort (indices_scores.begin (), indices_scores.end (), sortIndexScoresOp);</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160; </div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;        <span class="comment">/*</span></div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;<span class="comment">         * There might be duplicated candidates, in those cases it makes sense to take</span></div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;<span class="comment">         * the closer one in descriptor space</span></div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;<span class="comment">         */</span></div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160; </div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;        <span class="keyword">typename</span> std::map&lt;flann_model, bool&gt; found;</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;        <span class="keyword">typename</span> std::map&lt;flann_model, bool&gt;::iterator it_map;</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; indices_scores.size (); i++)</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;        {</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;          flann_model m = flann_models_[indices_scores[i].idx_models_];</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;          it_map = found.find (m);</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;          <span class="keywordflow">if</span> (it_map == found.end ())</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;          {</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;            indices_scores[found.size ()] = indices_scores[i];</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;            found[m] = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;          }</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;        }</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;        indices_scores.resize (found.size ());</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160; </div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;        <span class="keywordtype">int</span> num_n = std::min (NN_, <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (indices_scores.size ()));</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160; </div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;        <span class="comment">/*</span></div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;<span class="comment">         * Filter some hypothesis regarding to their distance to the first neighbour</span></div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;<span class="comment">         */</span></div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160; </div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;        <span class="comment">/*std::vector&lt;index_score&gt; indices_scores_filtered;</span></div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;<span class="comment">         indices_scores_filtered.resize (num_n);</span></div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;<span class="comment">         indices_scores_filtered[0] = indices_scores[0];</span></div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;<span class="comment">         float best_score = indices_scores[0].score_;</span></div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;<span class="comment">         int kept = 1;</span></div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;<span class="comment">         for (int i = 1; i &lt; num_n; ++i)</span></div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;<span class="comment">         {</span></div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;<span class="comment">         //std::cout &lt;&lt; best_score &lt;&lt; indices_scores[i].score_ &lt;&lt; (best_score / indices_scores[i].score_) &lt;&lt; std::endl;</span></div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;<span class="comment">         if ((best_score / indices_scores[i].score_) &gt; 0.65)</span></div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;<span class="comment">         {</span></div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;<span class="comment">         indices_scores_filtered[i] = indices_scores[i];</span></div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;<span class="comment">         kept++;</span></div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;<span class="comment">         }</span></div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;<span class="comment">         //best_score = indices_scores[i].score_;</span></div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;<span class="comment">         }</span></div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;<span class="comment">         indices_scores_filtered.resize (kept);</span></div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;<span class="comment">         //std::cout &lt;&lt; indices_scores_filtered.size () &lt;&lt; &quot; § &quot; &lt;&lt; num_n &lt;&lt; std::endl;</span></div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;<span class="comment">         indices_scores = indices_scores_filtered;</span></div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;<span class="comment">         num_n = indices_scores.size ();*/</span></div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot;Number of object hypotheses... &quot;</span> &lt;&lt; num_n &lt;&lt; std::endl;</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160; </div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;        std::vector&lt;bool&gt; valid_trans;</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;        std::vector &lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt; transformations;</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160; </div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8cfe49751fd78df3ea0591e380b8ef9d">micvfh_estimator_</a>-&gt;getValidTransformsVec (valid_trans);</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8cfe49751fd78df3ea0591e380b8ef9d">micvfh_estimator_</a>-&gt;getTransformsVec (transformations);</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160; </div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; num_n; ++i)</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;        {</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;          ModelT m = flann_models_[indices_scores[i].idx_models_].model;</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;          <span class="keywordtype">int</span> view_id = flann_models_[indices_scores[i].idx_models_].view_id;</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;          <span class="keywordtype">int</span> desc_id = flann_models_[indices_scores[i].idx_models_].descriptor_id;</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160; </div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;          <span class="keywordtype">int</span> idx_input = indices_scores[i].idx_input_;</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160; </div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;          std::cout &lt;&lt; m.class_ &lt;&lt; <span class="stringliteral">&quot;/&quot;</span> &lt;&lt; m.id_ &lt;&lt; <span class="stringliteral">&quot; ==&gt; &quot;</span> &lt;&lt; indices_scores[i].score_ &lt;&lt; std::endl;</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160; </div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;          Eigen::Matrix4f roll_view_pose;</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;          <span class="keywordtype">bool</span> roll_pose_found = getRollPose (m, view_id, desc_id, roll_view_pose);</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160; </div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;          <span class="keywordflow">if</span> (roll_pose_found &amp;&amp; valid_trans[idx_input])</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;          {</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;            Eigen::Matrix4f transposed = roll_view_pose.transpose ();</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160; </div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;            <span class="comment">//std::cout &lt;&lt; transposed &lt;&lt; std::endl;</span></div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160; </div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;            PointInTPtr view;</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;            getView (m, view_id, view);</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160; </div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;            Eigen::Matrix4f model_view_pose;</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;            getPose (m, view_id, model_view_pose);</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160; </div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;            Eigen::Matrix4f scale_mat;</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;            scale_mat.setIdentity (4, 4);</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160; </div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;            <span class="keywordflow">if</span> (compute_scale_)</div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;            {</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;              <span class="comment">//compute scale using the whole view</span></div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;              PointInTPtr view_transformed (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;              Eigen::Matrix4f hom_from_OVC_to_CC;</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;              hom_from_OVC_to_CC = transformations[idx_input].inverse () * transposed;</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;              <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*view, *view_transformed, hom_from_OVC_to_CC);</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160; </div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;              Eigen::Vector3f input_centroid = centroids[indices_scores[i].idx_input_];</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;              Eigen::Vector3f view_centroid;</div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;              getCentroid (m, view_id, desc_id, view_centroid);</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160; </div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;              Eigen::Vector4f cmatch4f (view_centroid[0], view_centroid[1], view_centroid[2], 0);</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;              Eigen::Vector4f cinput4f (input_centroid[0], input_centroid[1], input_centroid[2], 0);</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160; </div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;              Eigen::Vector4f max_pt_input;</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;              <a class="code" href="group__common.html#ga1583a71aef0f54550adef0ebfef89edd">pcl::getMaxDistance</a> (*processed, cinput4f, max_pt_input);</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;              max_pt_input[3] = 0;</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;              <span class="keywordtype">float</span> max_dist_input = (cinput4f - max_pt_input).norm ();</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160; </div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;              <span class="comment">//compute max dist for transformed model_view</span></div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;              <a class="code" href="group__common.html#ga1583a71aef0f54550adef0ebfef89edd">pcl::getMaxDistance</a> (*view, cmatch4f, max_pt_input);</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;              max_pt_input[3] = 0;</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;              <span class="keywordtype">float</span> max_dist_view = (cmatch4f - max_pt_input).norm ();</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160; </div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;              cmatch4f = hom_from_OVC_to_CC * cmatch4f;</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;              std::cout &lt;&lt; max_dist_view &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; max_dist_input &lt;&lt; std::endl;</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160; </div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;              <span class="keywordtype">float</span> scale_factor_view = max_dist_input / max_dist_view;</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;              std::cout &lt;&lt; <span class="stringliteral">&quot;Scale factor:&quot;</span> &lt;&lt; scale_factor_view &lt;&lt; std::endl;</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160; </div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;              Eigen::Matrix4f center, center_inv;</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160; </div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;              center.setIdentity (4, 4);</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;              center (0, 3) = -cinput4f[0];</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;              center (1, 3) = -cinput4f[1];</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;              center (2, 3) = -cinput4f[2];</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160; </div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;              center_inv.setIdentity (4, 4);</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;              center_inv (0, 3) = cinput4f[0];</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;              center_inv (1, 3) = cinput4f[1];</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;              center_inv (2, 3) = cinput4f[2];</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160; </div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;              scale_mat (0, 0) = scale_factor_view;</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;              scale_mat (1, 1) = scale_factor_view;</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;              scale_mat (2, 2) = scale_factor_view;</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160; </div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;              scale_mat = center_inv * scale_mat * center;</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;            }</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160; </div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;            Eigen::Matrix4f hom_from_OC_to_CC;</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;            hom_from_OC_to_CC = scale_mat * transformations[idx_input].inverse () * transposed * model_view_pose;</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160; </div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;            models_-&gt;push_back (m);</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;            transforms_-&gt;push_back (hom_from_OC_to_CC);</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;            descriptor_distances_.push_back (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (indices_scores[i].score_));</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;          }</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;          <span class="keywordflow">else</span></div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;          {</div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;            PCL_WARN(<span class="stringliteral">&quot;The roll pose was not found, should use CRH here... \n&quot;</span>);</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;          }</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;        }</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;      }</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160; </div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;      std::cout &lt;&lt; <span class="stringliteral">&quot;Number of object hypotheses:&quot;</span> &lt;&lt; models_-&gt;size () &lt;&lt; std::endl;</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160; </div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;      <span class="keywordflow">if</span> (ICP_iterations_ &gt; 0)</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;      {</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;        <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Pose refinement&quot;</span>);</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160; </div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;        <span class="comment">//Prepare scene and model clouds for the pose refinement step</span></div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;        <span class="keywordtype">float</span> VOXEL_SIZE_ICP_ = 0.005f;</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;        PointInTPtr cloud_voxelized_icp (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a> ());</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160; </div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;        {</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;          <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Voxelize stuff...&quot;</span>);</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;          <a class="code" href="classpcl_1_1_voxel_grid.html">pcl::VoxelGrid&lt;PointInT&gt;</a> voxel_grid_icp;</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;          voxel_grid_icp.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (processed);</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;          voxel_grid_icp.<a class="code" href="classpcl_1_1_voxel_grid.html#aa5d7831e665977bdce76ed05bd0005cf">setLeafSize</a> (VOXEL_SIZE_ICP_, VOXEL_SIZE_ICP_, VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;          voxel_grid_icp.<a class="code" href="classpcl_1_1_filter.html#a17115897ca28f6b12950d023958aa641">filter</a> (*cloud_voxelized_icp);</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;          <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a7e36f4e66c41b0327cd8bd63ce2de9dd">source_</a>-&gt;voxelizeAllModels (VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;        }</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160; </div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;<span class="preprocessor">#pragma omp parallel for num_threads(omp_get_num_procs())</span></div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; static_cast&lt;int&gt; (models_-&gt;size ()); i++)</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;        {</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160; </div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;          ConstPointInTPtr model_cloud;</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;          PointInTPtr model_aligned (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160; </div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;          <span class="keywordflow">if</span> (compute_scale_)</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;          {</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;            model_cloud = models_-&gt;at (i).getAssembled (-1);</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;            PointInTPtr model_aligned_m (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;            <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*model_cloud, *model_aligned_m, transforms_-&gt;at (i));</div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;            <a class="code" href="classpcl_1_1_voxel_grid.html">pcl::VoxelGrid&lt;PointInT&gt;</a> voxel_grid_icp;</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;            voxel_grid_icp.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (model_aligned_m);</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;            voxel_grid_icp.<a class="code" href="classpcl_1_1_voxel_grid.html#aa5d7831e665977bdce76ed05bd0005cf">setLeafSize</a> (VOXEL_SIZE_ICP_, VOXEL_SIZE_ICP_, VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;            voxel_grid_icp.<a class="code" href="classpcl_1_1_filter.html#a17115897ca28f6b12950d023958aa641">filter</a> (*model_aligned);</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;          }</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;          <span class="keywordflow">else</span></div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;          {</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;            model_cloud = models_-&gt;at (i).getAssembled (VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;            <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*model_cloud, *model_aligned, transforms_-&gt;at (i));</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;          }</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160; </div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;          <a class="code" href="classpcl_1_1_iterative_closest_point.html">pcl::IterativeClosestPoint&lt;PointInT, PointInT&gt;</a> reg;</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;          reg.<a class="code" href="classpcl_1_1_iterative_closest_point.html#ad5215429e057c8760ac48e9bdb09b12c">setInputSource</a> (model_aligned); <span class="comment">//model</span></div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;          reg.<a class="code" href="classpcl_1_1_iterative_closest_point.html#a8876f743cc31471a975e950e66c179d4">setInputTarget</a> (cloud_voxelized_icp); <span class="comment">//scene</span></div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#a3844d186f7a99d15464368e0f25635ed">setMaximumIterations</a> (ICP_iterations_);</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#a65596dcc3cb5d2647857226fb3d999a5">setMaxCorrespondenceDistance</a> (VOXEL_SIZE_ICP_ * 3.f);</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#aec74ab878cca8d62fd1be9942685a8c1">setTransformationEpsilon</a> (1e-6);</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160; </div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;          <span class="keyword">typename</span> pcl::PointCloud&lt;PointInT&gt;::Ptr output_ (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a> ());</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#a96212303ca16b6d60020824086887c4f">align</a> (*output_);</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160; </div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;          Eigen::Matrix4f icp_trans = reg.<a class="code" href="classpcl_1_1_registration.html#a1e68bd39ac943131dcbf1431f9afe3f3">getFinalTransformation</a> ();</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;          transforms_-&gt;at (i) = icp_trans * transforms_-&gt;at (i);</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;        }</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;      }</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160; </div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8eb34f1ab4617a891153c72e8cc0a3c8">hv_algorithm_</a>)</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;      {</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160; </div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;        <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;HYPOTHESES VERIFICATION&quot;</span>);</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160; </div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;        std::vector&lt;typename pcl::PointCloud&lt;PointInT&gt;::ConstPtr&gt; aligned_models;</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;        aligned_models.resize (models_-&gt;size ());</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160; </div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; models_-&gt;size (); i++)</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;        {</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;          ConstPointInTPtr model_cloud;</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;          PointInTPtr model_aligned (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160; </div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;          <span class="keywordflow">if</span> (compute_scale_)</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;          {</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;            model_cloud = models_-&gt;at (i).getAssembled (-1);</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;            PointInTPtr model_aligned_m (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;            <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*model_cloud, *model_aligned_m, transforms_-&gt;at (i));</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;            <a class="code" href="classpcl_1_1_voxel_grid.html">pcl::VoxelGrid&lt;PointInT&gt;</a> voxel_grid_icp;</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;            voxel_grid_icp.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (model_aligned_m);</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;            voxel_grid_icp.<a class="code" href="classpcl_1_1_voxel_grid.html#aa5d7831e665977bdce76ed05bd0005cf">setLeafSize</a> (0.005f, 0.005f, 0.005f);</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;            voxel_grid_icp.<a class="code" href="classpcl_1_1_filter.html#a17115897ca28f6b12950d023958aa641">filter</a> (*model_aligned);</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;          }</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;          <span class="keywordflow">else</span></div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;          {</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;            model_cloud = models_-&gt;at (i).getAssembled (0.005f);</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;            <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*model_cloud, *model_aligned, transforms_-&gt;at (i));</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;          }</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160; </div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;          <span class="comment">//ConstPointInTPtr model_cloud = models_-&gt;at (i).getAssembled (0.005f);</span></div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;          <span class="comment">//PointInTPtr model_aligned (new pcl::PointCloud&lt;PointInT&gt;);</span></div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;          <span class="comment">//pcl::transformPointCloud (*model_cloud, *model_aligned, transforms_-&gt;at (i));</span></div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;          aligned_models[i] = model_aligned;</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;        }</div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160; </div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;        std::vector&lt;bool&gt; mask_hv;</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8eb34f1ab4617a891153c72e8cc0a3c8">hv_algorithm_</a>-&gt;setSceneCloud (<a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a44090665a54a815539d3bf286cfe00be">input_</a>);</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8eb34f1ab4617a891153c72e8cc0a3c8">hv_algorithm_</a>-&gt;addModels (aligned_models, <span class="keyword">true</span>);</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8eb34f1ab4617a891153c72e8cc0a3c8">hv_algorithm_</a>-&gt;verify ();</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8eb34f1ab4617a891153c72e8cc0a3c8">hv_algorithm_</a>-&gt;getMask (mask_hv);</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160; </div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;        boost::shared_ptr &lt; std::vector&lt;ModelT&gt; &gt; models_temp;</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;        boost::shared_ptr &lt; std::vector&lt;Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt; &gt; transforms_temp;</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160; </div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;        models_temp.reset (<span class="keyword">new</span> std::vector&lt;ModelT&gt;);</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;        transforms_temp.reset (<span class="keyword">new</span> std::vector&lt;Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt;);</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160; </div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; models_-&gt;size (); i++)</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;        {</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;          <span class="keywordflow">if</span> (!mask_hv[i])</div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;            <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160; </div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;          models_temp-&gt;push_back (models_-&gt;at (i));</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;          transforms_temp-&gt;push_back (transforms_-&gt;at (i));</div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;        }</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160; </div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;        models_ = models_temp;</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;        transforms_ = transforms_temp;</div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;      }</div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160; </div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;    }</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;  }</div>
<div class="ttc" id="aclassflann_1_1_matrix_html"><div class="ttname"><a href="classflann_1_1_matrix.html">flann::Matrix</a></div><div class="ttdef"><b>Definition:</b> flann_search.h:51</div></div>
<div class="ttc" id="aclasspcl_1_1_filter_html_a17115897ca28f6b12950d023958aa641"><div class="ttname"><a href="classpcl_1_1_filter.html#a17115897ca28f6b12950d023958aa641">pcl::Filter::filter</a></div><div class="ttdeci">void filter(PointCloud &amp;output)</div><div class="ttdoc">Calls the filtering method and returns the filtered dataset in output.</div><div class="ttdef"><b>Definition:</b> filter.h:132</div></div>
<div class="ttc" id="aclasspcl_1_1_iterative_closest_point_html"><div class="ttname"><a href="classpcl_1_1_iterative_closest_point.html">pcl::IterativeClosestPoint</a></div><div class="ttdoc">IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm....</div><div class="ttdef"><b>Definition:</b> icp.h:95</div></div>
<div class="ttc" id="aclasspcl_1_1_iterative_closest_point_html_a8876f743cc31471a975e950e66c179d4"><div class="ttname"><a href="classpcl_1_1_iterative_closest_point.html#a8876f743cc31471a975e950e66c179d4">pcl::IterativeClosestPoint::setInputTarget</a></div><div class="ttdeci">virtual void setInputTarget(const PointCloudTargetConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input target (e.g., the point cloud that we want to align to the target)</div><div class="ttdef"><b>Definition:</b> icp.h:212</div></div>
<div class="ttc" id="aclasspcl_1_1_iterative_closest_point_html_ad5215429e057c8760ac48e9bdb09b12c"><div class="ttname"><a href="classpcl_1_1_iterative_closest_point.html#ad5215429e057c8760ac48e9bdb09b12c">pcl::IterativeClosestPoint::setInputSource</a></div><div class="ttdeci">virtual void setInputSource(const PointCloudSourceConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)</div><div class="ttdef"><b>Definition:</b> icp.h:177</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a1952d7101f3942bac3b69ed55c1ca7ea"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">pcl::PCLBase::setInputCloud</a></div><div class="ttdeci">virtual void setInputCloud(const PointCloudConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input dataset</div><div class="ttdef"><b>Definition:</b> pcl_base.hpp:66</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt; PointInT &gt;</a></div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a1e68bd39ac943131dcbf1431f9afe3f3"><div class="ttname"><a href="classpcl_1_1_registration.html#a1e68bd39ac943131dcbf1431f9afe3f3">pcl::Registration::getFinalTransformation</a></div><div class="ttdeci">Matrix4 getFinalTransformation()</div><div class="ttdoc">Get the final transformation matrix estimated by the registration method.</div><div class="ttdef"><b>Definition:</b> registration.h:275</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a3844d186f7a99d15464368e0f25635ed"><div class="ttname"><a href="classpcl_1_1_registration.html#a3844d186f7a99d15464368e0f25635ed">pcl::Registration::setMaximumIterations</a></div><div class="ttdeci">void setMaximumIterations(int nr_iterations)</div><div class="ttdoc">Set the maximum number of iterations the internal optimization should run for.</div><div class="ttdef"><b>Definition:</b> registration.h:285</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a65596dcc3cb5d2647857226fb3d999a5"><div class="ttname"><a href="classpcl_1_1_registration.html#a65596dcc3cb5d2647857226fb3d999a5">pcl::Registration::setMaxCorrespondenceDistance</a></div><div class="ttdeci">void setMaxCorrespondenceDistance(double distance_threshold)</div><div class="ttdoc">Set the maximum distance threshold between two correspondent points in source &lt;-&gt; target....</div><div class="ttdef"><b>Definition:</b> registration.h:321</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a96212303ca16b6d60020824086887c4f"><div class="ttname"><a href="classpcl_1_1_registration.html#a96212303ca16b6d60020824086887c4f">pcl::Registration::align</a></div><div class="ttdeci">void align(PointCloudSource &amp;output)</div><div class="ttdoc">Call the registration algorithm which estimates the transformation and returns the transformed source...</div><div class="ttdef"><b>Definition:</b> registration.hpp:169</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_aec74ab878cca8d62fd1be9942685a8c1"><div class="ttname"><a href="classpcl_1_1_registration.html#aec74ab878cca8d62fd1be9942685a8c1">pcl::Registration::setTransformationEpsilon</a></div><div class="ttdeci">void setTransformationEpsilon(double epsilon)</div><div class="ttdoc">Set the transformation epsilon (maximum allowable difference between two consecutive transformations)...</div><div class="ttdef"><b>Definition:</b> registration.h:336</div></div>
<div class="ttc" id="aclasspcl_1_1_scope_time_html"><div class="ttname"><a href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a></div><div class="ttdoc">Class to measure the time spent in a scope</div><div class="ttdef"><b>Definition:</b> time.h:118</div></div>
<div class="ttc" id="aclasspcl_1_1_voxel_grid_html"><div class="ttname"><a href="classpcl_1_1_voxel_grid.html">pcl::VoxelGrid</a></div><div class="ttdoc">VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.</div><div class="ttdef"><b>Definition:</b> voxel_grid.h:179</div></div>
<div class="ttc" id="aclasspcl_1_1_voxel_grid_html_aa5d7831e665977bdce76ed05bd0005cf"><div class="ttname"><a href="classpcl_1_1_voxel_grid.html#aa5d7831e665977bdce76ed05bd0005cf">pcl::VoxelGrid::setLeafSize</a></div><div class="ttdeci">void setLeafSize(const Eigen::Vector4f &amp;leaf_size)</div><div class="ttdoc">Set the voxel grid leaf size.</div><div class="ttdef"><b>Definition:</b> voxel_grid.h:223</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_html_a44090665a54a815539d3bf286cfe00be"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a44090665a54a815539d3bf286cfe00be">pcl::rec_3d_framework::GlobalNNCVFHRecognizer::input_</a></div><div class="ttdeci">PointInTPtr input_</div><div class="ttdoc">Point cloud to be classified</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_cvfh.h:61</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_html_a7e36f4e66c41b0327cd8bd63ce2de9dd"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a7e36f4e66c41b0327cd8bd63ce2de9dd">pcl::rec_3d_framework::GlobalNNCVFHRecognizer::source_</a></div><div class="ttdeci">boost::shared_ptr&lt; pcl::rec_3d_framework::Source&lt; PointInT &gt; &gt; source_</div><div class="ttdoc">Model data source</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_cvfh.h:64</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_html_a8cfe49751fd78df3ea0591e380b8ef9d"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8cfe49751fd78df3ea0591e380b8ef9d">pcl::rec_3d_framework::GlobalNNCVFHRecognizer::micvfh_estimator_</a></div><div class="ttdeci">boost::shared_ptr&lt; OURCVFHEstimator&lt; PointInT, FeatureT &gt; &gt; micvfh_estimator_</div><div class="ttdoc">Computes a feature</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_cvfh.h:67</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer_html_a8eb34f1ab4617a891153c72e8cc0a3c8"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_v_f_h_recognizer.html#a8eb34f1ab4617a891153c72e8cc0a3c8">pcl::rec_3d_framework::GlobalNNCVFHRecognizer::hv_algorithm_</a></div><div class="ttdeci">boost::shared_ptr&lt; HypothesisVerification&lt; PointInT, PointInT &gt; &gt; hv_algorithm_</div><div class="ttdoc">Hypotheses verification algorithm</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_cvfh.h:70</div></div>
<div class="ttc" id="agroup__common_html_ga1583a71aef0f54550adef0ebfef89edd"><div class="ttname"><a href="group__common.html#ga1583a71aef0f54550adef0ebfef89edd">pcl::getMaxDistance</a></div><div class="ttdeci">void getMaxDistance(const pcl::PointCloud&lt; PointT &gt; &amp;cloud, const Eigen::Vector4f &amp;pivot_pt, Eigen::Vector4f &amp;max_pt)</div><div class="ttdoc">Get the point at maximum distance from a given point and a given pointcloud</div><div class="ttdef"><b>Definition:</b> common.hpp:130</div></div>
<div class="ttc" id="agroup__common_html_ga52d532f7f2b4d7bba78d13701d3a33d8"><div class="ttname"><a href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a></div><div class="ttdeci">void transformPointCloud(const pcl::PointCloud&lt; PointT &gt; &amp;cloud_in, pcl::PointCloud&lt; PointT &gt; &amp;cloud_out, const Eigen::Transform&lt; Scalar, 3, Eigen::Affine &gt; &amp;transform, bool copy_all_fields=true)</div><div class="ttdoc">Apply an affine transform defined by an Eigen Transform</div><div class="ttdef"><b>Definition:</b> transforms.hpp:42</div></div>
<div class="ttc" id="agroup__common_html_gaa65b1c8d782e7b776ae682679d2d948f"><div class="ttname"><a href="group__common.html#gaa65b1c8d782e7b776ae682679d2d948f">pcl::copyPointCloud</a></div><div class="ttdeci">PCL_EXPORTS void copyPointCloud(const pcl::PCLPointCloud2 &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, pcl::PCLPointCloud2 &amp;cloud_out)</div><div class="ttdoc">Extract the indices of a given point cloud as a new point cloud</div></div>
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